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--- |
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dataset_info: |
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features: |
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- name: sentences |
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dtype: string |
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- name: labels |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 19977137 |
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num_examples: 8712 |
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- name: test |
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num_bytes: 8607911 |
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num_examples: 3735 |
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download_size: 13060346 |
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dataset_size: 28585048 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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--- |
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## Dataset Summary |
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**SID Clustering (SIDClustring)** is a Persian (Farsi) dataset created for the **Clustering** task, specifically focusing on grouping academic articles. It is part of the [FaMTEB (Farsi Massive Text Embedding Benchmark)](https://huggingface.co/spaces/mteb/leaderboard). The dataset was constructed from scientific articles available on **SID (Scientific Information Database – sid.ir)**, categorized into 8 distinct domains reflecting academic disciplines. |
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* **Language(s):** Persian (Farsi) |
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* **Task(s):** Clustering (Document Clustering, Topic Modeling) |
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* **Source:** Crawled from the SID academic publication platform |
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* **Part of FaMTEB:** Yes |
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## Supported Tasks and Leaderboards |
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This dataset is designed to assess the ability of embedding models to perform document clustering—grouping articles into logical scientific categories. Results can be viewed on the [Persian MTEB Leaderboard](https://huggingface.co/spaces/mteb/leaderboard), under the Clustering task. |
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## Construction |
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1. Articles were collected by crawling the **sid.ir** platform. |
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2. For each article: |
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- The **title** and **abstract** were extracted. |
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- These were concatenated using two newline characters (`\n\n`) to form the document input. |
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3. Each document was assigned to one of 8 predefined SID categories. |
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4. The resulting dataset serves as a benchmark for evaluating unsupervised clustering performance. |
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## Data Splits |
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* **Train:** 8,712 samples |
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* **Development (Dev):** 0 samples |
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* **Test:** 3,735 samples |
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